Researcher profile

Jing Gao

Jing Gao contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate

hep-ph Artificial Intelligence Machine Learning physics.optics

Trust snapshot

Quick read

Trust 17 - UnverifiedVerification L1Unclaimed author

4works

0followers

4topics

4close collaborators

Actions

Decide how to stay connected

Follow researcher0

Claiming links this public author record to a researcher profile and unlocks direct collaboration workflows.

Direct collaboration

Open a focused conversation when the fit is right

Claim this author entity first to unlock direct invitations.

Inspect adjacent work, topics, institutions and collaborators without jumping out to a separate graph page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

preprint2026arXiv

A Vehicle-portable Ultra-stable Laser for Operating on Highways

Portable ultra-stable lasers are essential for high-precision measurements. This study presents a 1550 nm vehicle-portable ultra-stable laser designed for continuous real-time operation on highways. We implement several measures to mitigate environmental impacts, including active temperature control with a standard deviation of mK/day to reduce frequency drift of the optical reference cavity, all-polarization-maintaining fiber devices to enhance the robustness of the optical path, and highly integrated electronic units to diminish thermal effects. The performance of the ultra-stable laser is evaluated through real-time beat frequency measurements with another similar ultra-stable laser over a transport distance of approximately 100 km, encompassing rural roads, national roads, urban roads, and expressways. The results indicate frequency stability of approximately 10-12/(0.01s-100 s) during transport, about 5E-14/s while the vehicle is stationary with the engine running, and around 3E-15/s with the engine off, all without active vibration isolation. This work marks the first recorded instance of a portable ultra-stable laser achieving continuous real-time operation on highways and lays a crucial foundation for non-laboratory applications, such as mobile laser communication and dynamic free-space time-frequency comparison.

preprint2026arXiv

Strategic Over-Parameterization for Generalizable Low-Rank Adaptation

Adapting large language models (LLMs) to downstream tasks via full fine-tuning is increasingly impractical due to its computational and memory demands. Parameter-efficient fine-tuning (PEFT) approaches such as Low-Rank Adaptation (LoRA) mitigate this by confining updates to a compact set of trainable parameters, but this aggressive reduction often sacrifices generalization, especially under transfer across heterogeneous tasks and domains. We revisit the tension between parameter efficiency and adaptation capacity, and ask whether the two are truly at odds. We answer in the negative by introducing LoRA-Over, a framework grounded in a simple principle: enrich the optimization landscape during training, then collapse the enrichment at inference. LoRA-Over injects auxiliary parameters into the low-rank adapters during training to broaden the effective hypothesis space, and through a decomposition-based reformulation folds them back into a standard low-rank structure with negligible reconstruction error, keeping inference cost identical to vanilla LoRA. Since not all weight matrices benefit equally from added capacity, we further propose two scheduling strategies, one statically predefined and one dynamically determined at runtime, that direct extra capacity where most needed. We evaluate LoRA-Over on language understanding (GLUE, T5-Base), dialogue (MT-Bench), arithmetic reasoning (GSM8K), and code generation (HumanEval), using LLaMA 2-7B and LLaMA 3.1-8B. Across all benchmarks and scales, LoRA-Over consistently outperforms vanilla LoRA, showing that principled over-parameterization designed to vanish at inference is an effective lever for improving PEFT generalization. Code will be released upon acceptance.

preprint2026arXiv

Study of $CP$ violation in $Λ_b^0/Ξ^-_b\rightarrow Λ(1520)M$ decays with the final-state rescattering mechanism

Recently, the LHCb collaboration reported the first observation of $CP$ violation in baryon decays, with a significance of more than $5σ$. This strongly motivates us to investigate the $CP$ violation in more baryon decay processes. In this work, we employ the final-state rescattering mechanism with introducing two model parameters, $Λ_{charm}$ and $Λ_{charmless}$, and calculate two-body non-leptonic baryon decays $Λ^0_b \rightarrow Λ(1520)\,π^0/κ(700)/f_0(500, 980)/ρ^0/K^{*0}/ϕ$ and $Ξ^-_b \rightarrow Λ(1520)\,K^-$. Consequently, we evaluate the corresponding branching ratios, $CP$ asymmetries, and interference effects between different decay amplitudes. Our theoretical predictions for certain decay channels are in good agreement with current experimental measurements, while the remaining processes--particularly the remarkably large $CP$ violation observable revealed by the kinematic analysis are expected to be tested in future experiments.

preprint2026arXiv

Study of $CP$ violation in $Λ_b^0\rightarrow N^*M$ decays with the final-state rescattering mechanism

In this work, we investigate the charmless non-leptonic two-body $Λ_b$ decays within the framework of final-state rescattering mechanism. In contrast to the Cutkosky cutting method, we compute both the absorptive and dispersive parts of the hadronic rescattering triangle diagrams. Based on the established formalism, we analyze the $Λ_b \to N^*(1535,1520)M$ decay processes with $M =K_S, K^*_0(700)$, $f_0(500,980), ρ(770), \bar{K}^{*0}$, $ϕ$, and predict various physical observables, such as their branching ratios, direct and partial-wave $CP$ asymmetries, as well as decay asymmetry parameters. These two-body decay processes are expected to contribute primarily to the subsequent four-body decay channels, such as $Λ_b^0 \to p\,π^-\,π^+\,π^-$, whose $CP$ asymmetry measurements will be accessible at the LHCb experiment.

Institution

Affiliation not imported yet

This author record came from a source that does not expose affiliation metadata. Once the author claims the profile or we enrich the record from another provider, this section will link to the concrete institution.

Topic footprint